FRUIT DETECTION AND CALORIE ESTIMATION USING RASPBERRY PI
Subhiksha.K
, K.Jahnavi , Anisha.G , Yamka delfin .A , A.Kalaimani
neural network(NN), convolutional neural network(CNN)
Information on the advancements in the field of health management is provided by this initiative. Fruit ripeness estimation methods are now extensively used in digital picture processing. The goal of this study was to investigate the various feature extraction algorithms and techniques currently in use for eliminating features from digital photos that have been captured. The quality of the fruits must therefore be marked on the packaging by the vendors. In this study, the weight, size, form, and colour of the fruit are used to assess its quality. All of these algorithms are implemented on the Raspberry Pi development board, which will eventually become a stand- alone and reasonably priced gadget.A cost-effective embedded system prototype for determining the size, shape, and colour of the fruit will be created by carrying out all of the component interfaces. Other fruits can use the same approach as well. Different classifiers have been categorised according to their benefits and drawbacks. In addition, this fruit detector is applied to fruit calorie estimation for fruit photos. We use NN as a fruit detector to detect each fruit image, and the fruit calorie of each detected fruit are estimated by image-based fruit calorie estimation. In this way, we estimate fruit calories from a fruit photo of multiple fruit. In this experiment, we collect fruit photos of multiple fruit with total fruit calorie of multiple fruit. Then we estimate fruit calories from fruit photos of multiple fruit by combining the fruit detector and image based fruit calorie estimation.It was discovered that a compromise between high computing complexity and great precision was required.
"FRUIT DETECTION AND CALORIE ESTIMATION USING RASPBERRY PI", TIJER - TIJER - INTERNATIONAL RESEARCH JOURNAL (www.TIJER.org), ISSN:2349-9249, Vol.11, Issue 2, page no.1026-1030, February-2024, Available :https://tijer.org/TIJER/papers/TIJERB001167.pdf
Volume 11
Issue 2,
February-2024
Pages : 1026-1030
Paper Reg. ID: TIJER_151109
Published Paper Id: TIJERB001167
Downloads: 000278
Research Area: Science and Technology
Country: Thiruvallur,Chennai, Tamil Nadu, India
ISSN: 2349-9249 | IMPACT FACTOR: 8.57 Calculated By Google Scholar | ESTD YEAR: 2014
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.57 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: TIJER (IJ Publication) Janvi Wave
